review_code_quality

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the burden. It transparently states it performs deterministic static analysis (implying read-only), explains that it does not create new judgments but only prioritizes existing signals, and describes how results are communicated. This is strong transparency, though it doesn't explicitly mention side effects or output format beyond 'traffic light'.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise and to the point, using two sentences to cover purpose, behavior, and parameters. No redundant or vague wording.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given that there is no output schema, the description sufficiently conveys what the tool does and the nature of its output (signals explained in plain language with priorities). It could be more explicit about the exact result format, but it's adequate for an agent to understand the tool's functionality.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Despite zero schema description coverage, the description explains both parameters: 'path' is the absolute directory to analyze, and 'hub_threshold' is the hub detection connection count threshold with 0 meaning auto-compute. This fully compensates for the schema's lack of detail, adding meaningful context.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool reviews structural smells (cycles, hubs, isolation, folder boundaries) and presents them as a traffic light. It also distinguishes itself from LLM-based assessment, providing a specific and unambiguous purpose.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides some usage context (deterministic static analysis, not LLM-based) but does not explicitly compare with sibling tools like analyze_structure or extract_dependency_graph. It lacks explicit 'when to use vs alternatives' guidance, so it's only partially helpful.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.